Cooperative customer navigation between robots outside and inside a retail shop—an implementation on the ubiquitous market platform

  • Koji Kamei
  • Tetsushi Ikeda
  • Masahiro Shiomi
  • Hiroyuki Kidokoro
  • Akira Utsumi
  • Kazuhiko Shinozawa
  • Takahiro Miyashita
  • Norihiro Hagita
Article

Abstract

Applying the technologies of a network robot system, recommendation methods used in e-commerce are incorporated in a retail shop in the real world. We constructed a platform for ubiquitous networked robots that focuses on a shop environment where communication robots perform customer navigation. The platform observes customers’ purchasing behavior by networked sensors, including a laser range finder-based human position tracking system, and then controls visible-type communication robots in the environment to perform customer navigation. Two types of navigation scenarios are implemented and investigated in experiments using 80 participants. The results indicate that the participants in the cooperative navigation scenario, who interacted with communication robots located both outside and inside the shop, felt friendliness toward the robots and found it easy to understand what the robots said.

Keywords

Network robot system Human position tracking Persuasive technology Recommendation 

References

  1. 1.
    Broder A, Fontoura M, Josifovski V, Riedel L (2007) A semantic approach to contextual advertising. In: Proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval (SIGIR07), pp 559–566Google Scholar
  2. 2.
    Decker C, Kubach U, Beigl M (2003) Revealing the retail black box by interaction sensing. In: Proceedings of the distributed computing system 2003, pp 328–333Google Scholar
  3. 3.
    Glas DF, Miyashita T, Ishiguro H, Hagita N (2009) Laser-based tracking of human position and orientation using parametric shape modeling. Adv Robot 23:405–428CrossRefGoogle Scholar
  4. 4.
    Häubl G, Murray KB (2001) Recommending or persuading?: the impact of a shopping agent’s algorithm on user behavior. In: Proceedings of the 3rd ACM conference on electronic commerce (EC01), pp 163–170Google Scholar
  5. 5.
    Häubl G, Murray KB (2006) Double agents. MIT Sloan Manag Rev 47(3):8–12Google Scholar
  6. 6.
    Hui SK, Bradlow ET, Fader PS (2009) Testing behavioral hypotheses using an integrated model of grocery store shopping path and purchase behavior. J Consum Res 36(3):478–493CrossRefGoogle Scholar
  7. 7.
    Kamei K et al (2010) Recommendation from robots in a real-world reatail shop. In: Proceedings of the international conference on multimodal interfaces and the workshop on machine learning for multimodal interaction, ICMI-MLMI ’10, pp 19:1–19:8Google Scholar
  8. 8.
    Kamei K et al (2011) Effectiveness of cooperative customer navigation from robots around a retail shop. In: Proceedings of the 2011 IEEE third international conference on social computing, socialCom 2011, pp 235–241Google Scholar
  9. 9.
    Kamei K, Sato M, Nishio S, Hagita N (2012) Cloud networked robotics. IEEE Netw 26(3):28–34CrossRefGoogle Scholar
  10. 10.
    Kanda T et al (2010) A communication robot in a shopping mall. IEEE Trans Robot 26(5):897–913CrossRefGoogle Scholar
  11. 11.
    Kidokoro H, Kamei K, Shinozawa K, Miyashita T, Hagita N (2011) You stopped by there? I recommend this: changing customer behaviors with robots. In: Proceedings of the thirteenth international conference on ubiquitous computing (UbiComp2011), pp 569–570Google Scholar
  12. 12.
    Larson JS, Bradlow ET, Fader PS (2005) An exploratory look at supermarket shopping paths. Res Mark 22(4):395–414CrossRefGoogle Scholar
  13. 13.
    Sanfeliu A et al (2010) Decentralized sensor fusion for ubiquitous networking robotics in urban areas. Sensors 10(3):2274–2314CrossRefGoogle Scholar
  14. 14.
    Sanfeliu A, Hagita N, Saffiotti A (2008) Network robot systems. Robot Auton Syst 56(10):793–797CrossRefGoogle Scholar
  15. 15.
    Sato M, Kamei K, Nishio S, Hagita N (2011) The ubiquitous network robot platform: common platform for continuous daily robotic services. In: Proceedings of the 2011 IEEE/SICE international symposium on system integration (SII2011), pp 318–323Google Scholar
  16. 16.
    Schafer JB, Konstan J, Riedi J (1999) Recommender systems in e-commerce. In: Proceedings of the 1st ACM conference on electronic commerce (EC99), pp 158–166Google Scholar
  17. 17.
    Shinozawa K, Naya F, Yamato J, Kogure K (2005) Differences in robot and screen agent recommendations on human decision-making. Int J Hum-Comput St 62(2):267–279CrossRefGoogle Scholar
  18. 18.
    Tenorth M et al (2011) Web-enabled robot. IEEE Robot Autom Mag 18(2):58–68MathSciNetCrossRefGoogle Scholar
  19. 19.
    Underhill P (2008) Why we buy: the science of shopping—updated and reviced for the internet, the global consumer, and beyond. Simon & Schuster, New YorkGoogle Scholar
  20. 20.
    Waibel M et al (2011) RoboEarth. IEEE Robot Autom Mag 18(2):69–82CrossRefGoogle Scholar
  21. 21.
    Yamazoe H, Utsumi A, Yonezawa T, Abe S (2008) Remote gaze estimation with a single camera based on facial-feature tracking without special calibration actions. In: Proceedings of the eye tracking research & applications symposium (ETRA2008), pp 245–250Google Scholar

Copyright information

© Institut Mines-Télécom and Springer-Verlag 2012

Authors and Affiliations

  • Koji Kamei
    • 1
  • Tetsushi Ikeda
    • 1
  • Masahiro Shiomi
    • 1
  • Hiroyuki Kidokoro
    • 1
  • Akira Utsumi
    • 1
  • Kazuhiko Shinozawa
    • 1
  • Takahiro Miyashita
    • 1
  • Norihiro Hagita
    • 1
  1. 1.ATR Intelligent Robotics and Communication LaboratoriesKyotoJapan

Personalised recommendations